InSb alloy was prepared then InSb:Bi films have been prepared successfully by thermal evaporation technique on glass substrate at Ts=423K. The variation of activation energies(Ea1,Ea2)of d.c conductivity with annealing temperature (303, 373, 423, 473, 523 and 573)K were measured, it is found that its values increases with increasing annealing temperature. To show the type of the films, the Hall and thermoelectric power were measured. The activation energy of the thermoelectric power is much smaller than for d.c conductivity and increases with increasing annealing temperature .The mobility and carrier concentration has been measured also.

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

The structural, optical and electrical properties of ZnS films prepared by vacuum evaporation technique on glass substrate at room temperature and treated at different annealing temperatures (323, 373, 423)K of thickness (0.5)µm have been studied. The structure of these films is determined by X-ray diffraction (XRD). The X-ray diffraction studies show that the structure is polycrystalline with cubic structure, and there are strong peaks at the direction (111). The optical properties investigated which include the absorbance and transmittance spectra, energy band gab, absorption coefficient, and other optical constants. The results showed that films have direct optical transition. The optical band gab was found to be in the range t

The ceramic compound Mg1-xSixAl2O4 (x= 0, 0.1, 0.2, 0.3, 0.4) was prepared from nano powder of Al2O3 and MgO doped with Nano powder of SiO2 at different molar ratios. The specimens were prepared by standard chemical solid reaction technique and sintered at 1450 oC. Structure of the specimens was analyzed by using X-ray diffraction (XRD). The X-ray patterns of the specimens showed the formation of pure simple cubic spinel structure MgAl2O4 phase with space group of ̅ . The average grain size and surface topology were studied by atomic force microscopy. The results showed that the average grain size was about 73-90 nm. The DC electrical properties of the specimen were measured. The apparent density was found to increase and the porosity a

A polycrystalline CdTefilms have been prepared by thermal evaporation technique on glass substrate at room temperature. The films thickness was about700±50 nm. Some of these films were annealed at 573 K for different duration times (60, 120 and 180 minutes), and other CdTe films followed by a layer of CdCl₂ which has been deposited on them, and then the prepared CdTe films with CdCl₂ layer have been annealed for the same conditions. The structures of CdTe films without and with CdCl₂ layer have been investigated by X-ray diffraction. The as prepared and annealed films without and with CdCl₂ layer were polycrystalline structure with preferred orientation at (111) plane. The better structural pr

Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

thin films of se:2.5% as were deposited on a glass substates by thermal coevaporation techniqi=ue under high vacuum at different thikness

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data